AIMC Topic: Bacteria

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Colonial bacterial memetic algorithm and its application on a darts playing robot.

Scientific reports Mar 28, 2025
In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. CBMA extends the Bacterial Memetic Algorithm by integrating Cultural Algorithms and co-evolutionary dy...
Robotics Biological Evolution Algorithms Bacteria
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Machine learning assisted paper-based fluorescent sensor array with metal-doped multicolor carbon quantum dots for identification and inactivation of bacteria.

Talanta Mar 27, 2025
Bacterial infection is a thorny threat in a variety of fields, including medicine, environment, food, and agriculture. A multifunctional platform that meets the demands of both bacterial identification and real-time inactivation is urgently needed. T...
Anti-Bacterial Agents Silver Machine Learning Fluorescence Paper Zinc Carbon Fluorescent Dyes Biosensing Techniques Quantum Dots Bacteria Copper
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aurora: a machine learning gwas tool for analyzing microbial habitat adaptation.

Genome biology Mar 23, 2025
A primary goal of microbial genome-wide association studies is identifying genomic variants associated with a particular habitat. Existing tools fail to identify known causal variants if the analyzed trait shaped the phylogeny. Furthermore, due to in...
Phylogeny Genome-Wide Association Study Adaptation, Physiological Bacteria Machine Learning Software Ecosystem
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Artificial intelligence in bacterial diagnostics and antimicrobial susceptibility testing: Current advances and future prospects.

Biosensors & bioelectronics Mar 19, 2025
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. This review explores the role of AI in revolutionizing bacterial detection and antimicrobial suscept...
Humans Neural Networks, Computer Bacteria Support Vector Machine Anti-Bacterial Agents Biosensing Techniques Bacterial Infections Deep Learning Artificial Intelligence Microbial Sensitivity Tests Machine Learning
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Biofilm-mediated infections; novel therapeutic approaches and harnessing artificial intelligence for early detection and treatment of biofilm-associated infections.

Microbial pathogenesis Mar 19, 2025
A biofilm is a group of bacteria that have self-produced a matrix and are grouped together in a dense population. By resisting the host's immune system's phagocytosis process and attacking with anti-microbial chemicals such as reactive oxygen and nit...
Anti-Infective Agents Biofilms Bacteria Artificial Intelligence Anti-Bacterial Agents Early Diagnosis Nanoparticles Humans
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Revealing gut microbiota biomarkers associated with melanoma immunotherapy response and key bacteria-fungi interaction relationships: evidence from metagenomics, machine learning, and SHAP methodology.

Frontiers in immunology Mar 18, 2025
INTRODUCTION: The gut microbiota is associated with the response to immunotherapy in cutaneous melanoma (CM). However, gut fungal biomarkers and bacterial-fungal interactions have yet to be determined.
Skin Neoplasms Treatment Outcome Biomarkers Aged Gastrointestinal Microbiome Female Metagenomics Fungi Male Melanoma Bacteria Adult Middle Aged Humans Immunotherapy Machine Learning
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Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Computers in biology and medicine Mar 17, 2025
Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, including microorganisms. However, the hypothesis posits that implementing micro- and nanoscale DTs, e...
Neural Networks, Computer Algorithms Deep Learning Humans Internet of Things Federated Learning Convolutional Neural Networks Bacteria
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deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.

mSystems Mar 10, 2025
Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. They contain the 21st amino acid selenocysteine (Sec) in the active sites, which is encoded by an in-frame UGA codon. Compared to eukaryotes, identificat...
Deep Learning Bacteria Genome, Bacterial Bacterial Proteins Selenoproteins Algorithms
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Enhancing Bacterial Phenotype Classification Through the Integration of Autogating and Automated Machine Learning in Flow Cytometric Analysis.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Mar 10, 2025
Although flow cytometry produces reliable results, the data processing from gating to fingerprinting is prone to subjective bias. Here, we integrated autogating with Automated Machine Learning in flow cytometry to enhance the classification of bacter...
Bacteria Escherichia coli Machine Learning Phenotype Flow Cytometry
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Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.

Journal of environmental management Mar 9, 2025
Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associated with traditional detection methods. In recent years, researchers capitalized on this potential ...
Bacteria Sample Size Sewage Wastewater Algorithms Machine Learning
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